The popularity of graphics cards with their immensely powerful GPUs
(Graphic Processing Units) are causing the HPC world to look at graphics
card as the next big development. Today, NVIDIA announced a new product
line called Tesla a GPU aimed squarely at the HPC market. Read on to find out more about Tesla line of products (with pictures).

NVIDIA has just announced a new
GPGPU (General Purpose Graphics
Processing Unit) called
Tesla.
The Tesla includes a somewhat new processor called the
C870. Also
announced were a GPU Computing server called the
S870,
and a desk-side unit called the
D870

The new processor is called the C870 and is rumored to be a heavily
modified GeForce 8800GTX card. Here are the basic stats on it:

The C870 card is shown in Figure One.
Notice there is no video port on the card! But also notice that the heat
exhausts out though the mesh on the rear of the card. If you want to put
these cards in a node, be sure to put enough air flow over the card.

NVIDIA also announced two other products in the Tesla family. These product are just not graphics cards, but
basically co-processors for HPC nodes. NVIDIA introduced (Figure Two) the D870 which
is a desk-side unit that has up two C870 GPUs (1.0 TFLOPS of peak
performance).

Figure Two: Deskside with two C870 GPUs

You can connect the D870 to another system by using an NVIDIA PCI x8 or
x16 adapter card in the host node (this only adds about 10W of power
usage to the host node). Then it is connected to the D870
with a PCI-e cable. There is a switch inside that box that allows the
data to be sent to either of the GPUs. Note that
CUDA,
NVIDIA's GPGPU programming tools allow you to program or use both
GPUs transparently. With 2 GPUs, the D870 has a total of 3 GB of memory
that can be used. In addition, it is fairly quiet, producing only about
40 dB of noise (normal conversation can happen up to about 45-50 dBs).
It produces about 550W and has a list price of about $7,500.
D870 Deskside Supercomputer

The last product (Figure Three) that NVIDIA announced is the S870 which is similar
to the D870, but is designed to be attached to a rack-mounted node
with up to 4 GPUs (4+ TFLOPS peak performance).

Figure Three: Rack-mount with four GPUs

The S870 is a 1U rack-mount unit designed for normal 19" racks. It
connects to a host node in the same way that the D870 does. In the
standard configuration, the host node has 1 PCI-e adapter card driving
4 GPUs and there is an optional configuration of 2 PCI-e adapters in
the host node each driving 2 GPUs. There is also likely to be a future
model with 8 GPUs. The unit uses up to 800W at peak and will cost about
$12,000. It would only take 1 or 2 of these units to make the
Top500 (assuming peak performance).

Why Is This Announcement Significant?

Tesla was a bit
of a maverick during his time. His ideas and claims were considered
to be a bit outrageous leading to him being called a mad scientist, but
in many ways he was a genius. His
Power transmission
without wires development was demonstrated as early as 1891 and only
recently been duplicated. So Tesla is an appropriate
title for the project - new concepts that could lead to a transformation
in HPC.

This new product could be a real disruptive influence on HPC because of
the huge amount of computational power in a small, relatively low-power,
processor. There are already some
developments
where codes have been ported to GPUs with great success including one
example with saw about a 240X improvement performance. The NVIDIA CUDA
environment also allows you to develop using C and C++ tools and compilers
that many coders are used to. More over an important development is
that the C870 is IEEE 754 compliant. Other GPUs aren't really IEEE 754
compliant and this has caused problems with code development.

{mosgoogle right}

Equally significant is that both NVIDIA and AMD that make GPUs and graphics
cards are developing product for the HPC market. The HPC market is not
nearly as big as the graphics market so it is significant that these
companies have developed products for the HPC market. Granted the are
derivative products, but the fact that they consider the HPC market
worth chasing is note worthy. Equally noticeable is that the GPUs are
significantly faster than other co-processor options for HPC (such as
FPGA and Clearspeed). Yes, Tesla is currently single precision, but
a number of applications can take advantage of it. But, the rumor mill
says that NVIDIA should be coming out with a double-precision GPU
by the end of the year.

Finally, it should be noted that such astounding performance
is not available to every applications. Those that map well into
the GPU architecture should derive great benefit from these types of
applications.

Dr. Jeff Layton hopes to someday have a 20 TB file system or a
20 TFLOP system in his home computer (donations gladly accepted). It
will be interesting to see which one will happen first. He can
sometimes be found lounging at a nearby Fry's, dreaming of hardware and
drinking coffee (but never during working hours).